APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility

Background: It is well known that most of the binding free energy of protein interaction is contributed by a few key hot spot residues. These residues are crucial for understanding the function of proteins and studying their interactions. Experimental hot spots detection methods such as alanine scanning mutagenesis are not applicable on a large scale since they are time consuming and expensive. Therefore, reliable and efficient computational methods for identifying hot spots are greatly desired and urgently required. Results: In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces. We systematically investigate a wide variety of 62 features from a combination of protein sequence and structure information. Then, to remove redundant and irrelevant features and improve the prediction performance, feature selection is employed using the F-score method. Based on the selected features, nine individualfeature ...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Jun-Feng Xia, Xing-Ming Zhao, Jiangning Song, De-Shuang Huang
• Keywords: BMCBI 2010, Hot Spot, Key Hot Spot, Protein